The present invention relates in general to detection of faults in vehicle systems such as an engine, and more specifically to use of an averaging filter to reduce the possibility of false indications of a fault.
It is well known to monitor the operation of a vehicle system and/or component using a sensor to detect a performance parameter of the system or component. The performance parameter is then examined in order to detect a fault in the operation of the monitored system or component. For example, faults in an internal combustion engine resulting in engine misfire can be monitored by sensing engine crankshaft acceleration as described in U.S. Pat. Nos. 5,044,194; 5,044,195; 5,056,360; 5,095,742; 5,109,695; and 5,117,681. In another example, the efficiency of a catalytic converter is inferred by sensing oxygen storage in the exhaust flow based on exhaust gas oxygen (EGO) sensors.
Monitoring of the system or component to detect a fault produces a data stream corresponding to a performance parameter of the system or component that defines the presence of a fault to be detected. The data stream may be directly derived from the sensor data or may include parameter calculations using the sensor data. For example, in misfire detection, crankshaft velocity measurements are used in calculating crankshaft acceleration deviations which are then compared to an expected torque and a data stream identifying the results of the comparisons is generated as described in the above patents. The data stream for a misfire detector consists of only a couple of discrete values such as "0" to represent a proper firing and "1" to represent a misfire for an individual cylinder event. A fault is then determined by examining the misfire rate indicated by the data stream (the percent of misfires to total cylinder events). In the case of other diagnostic systems such as exhaust gas oxygen sensor and catalyst efficiency monitoring, the data stream is multivalued and the magnitude of the data is compared to a threshold which defines the presence of a fault.
The data stream characterizing a system or component inherently includes random error fluctuations that often can be characterized as Gaussian noise. The fluctuations can result in false detection of a fault. Therefore, the data stream is averaged to reduce false detections of faults since averaging reduces the effect of the random error fluctuations.
For purposes of performing an averaging function to produce a low probability of false fault detection while still maintaining a fast response time to the occurrence of a real fault, a geometric moving average (GMA) provides significant improvements over the conventional fixed window average (FWA), as described in co-pending application Ser. No. 08/042,257, filed on Apr. 2, 1993, hereby incorporated by reference. The advantage of the GMA over other averaging techniques is that it better balances the conflicting requirements of quick responsiveness to changes in the data stream being averaged while filtering out signal noise that could otherwise lead to a false fault detection.
An important characteristic of any averaging filter is its time constant. In a vehicle diagnostic system, the time constant of the averaging filter must be selected to be long enough to avoid false detection of a fault over the extending driving cycles of the vehicle (which may include an astronomical amount of data in the data stream such as for misfire detection with about 100 cylinder events each second). Due to the time constant, however, a certain delay is experienced in any change in the diagnostic output in response to a change in the data stream (i.e., from a no fault to a fault condition or vice versa).
In servicing of a vehicle, there may be a deliberate change made to the vehicle system or component being monitored, resulting in a corresponding change in the data stream values. It may be desired to monitor the resulting change in the diagnostic output to determine the effect of the deliberately introduced change on the vehicle system or component or even to test the functionality of the monitoring system itself. However, the delay in obtaining the updated diagnostic output may be undesirably long, especially in instances where the system or component produces a data stream value only once per driving cycle, for example.